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ORCIDTechnometrics, Volume 65
Volume 65, Number 1, January 2023
- V. Roshan Joseph:
Editor's Report. 1-3 - Annie Sauer, Robert B. Gramacy, David Higdon:
Active Learning for Deep Gaussian Process Surrogates. 4-18 - Ruiyu Xu, Jianguo Wu
, Xiaowei Yue, Yongxiang Li:
Online Structural Change-Point Detection of High-dimensional Streaming Data via Dynamic Sparse Subspace Learning. 19-32 - Wanrong Zhang, Yajun Mei:
Bandit Change-Point Detection for Real-Time Monitoring High-Dimensional Data Under Sampling Control. 33-43 - Haoyun Wang, Liyan Xie, Yao Xie, Alex Cuozzo, Simon Mak:
Sequential Change-Point Detection for Mutually Exciting Point Processes. 44-56 - Qiao Liang, Shyam Ranganathan, Kaibo Wang, Xinwei Deng:
JST-RR Model: Joint Modeling of Ratings and Reviews in Sentiment-Topic Prediction. 57-69 - Abhinav Prakash, Rui Tuo, Yu Ding:
The Temporal Overfitting Problem with Applications in Wind Power Curve Modeling. 70-82 - Heegeon Yoon, Heeyoung Kim:
Label-Noise Robust Deep Generative Model for Semi-Supervised Learning. 83-95 - Rakhi Singh, John Stufken:
Selection of Two-Level Supersaturated Designs for Main Effects Models. 96-104 - Benjamin Seiyon Lee, Jaewoo Park:
A Scalable Partitioned Approach to Model Massive Nonstationary Non-Gaussian Spatial Datasets. 105-116 - Xiaoqian Liu, Eric C. Chi, Kenneth Lange:
A Sharper Computational Tool for Regression. 117-126 - Firdous Ahmad Mala:
Geometry in Our Three-Dimensional World: by Alfred S. Posamentier, Bernd Thaller, Christian Dorner, Robert Geretschläger, Guenter Maresch, Christian Spreitzer, David Stuhlpfarrer, World Scientific, 2021, 440 pp., $118.00 (HB), ISBN 9789811237102. 127-129 - Mohieddine Rahmouni:
Dark Data: Why What You Don't Know Matters: by David J. Hand, Princeton, NJ: Princeton University Press, 2020, xii + 330 pp., ISBN 9780691182377. 129-131 - Firdous Ahmad Mala:
Vedic Mathematics: A Mathematical Tale from the Ancient Veda to Modern Times: by Giuseppe Dattoli, Silvia Licciardi, and Marcello Artioli, World Scientific, 2021, 232 pp., $68 (HB), ISBN 9789811221552. 131-132 - Roger M. Sauter:
Foundations of Statistics for Data Scientists: With R and Python: by Alan Agresti and Maria Kateri, Boca Raton, FL: Chapman and Hall/CRC, 2022, xv + 453 pp., $136.46 (hcb). 132-133 - Shuangzhe Liu:
Directional Statistics for Innovative Applications: A Bicentennial Tribute to Florence Nightingale: by Ashis SenGupta and Barry C. Arnold, Singapore: Springer, 2022, XIX, 488 pp., with 49 b/w illustrations, 93 illustrations in color, ISBN 978-981-19-1043-2 (hbk). 133-134 - Stan Lipovetsky:
Chance, Logic and Intuition: An Introduction to the Counter-Intuitive Logic of Chance: by Steven Tijms, Singapore: World Scientific, 2021, 256 pp., $34.00 (pbk), ISBN 978-981-124-783-5. 134-136
Volume 65, Number 2, April 2023
- Kungang Zhang, Anh Tuan Bui, Daniel W. Apley:
Concept Drift Monitoring and Diagnostics of Supervised Learning Models via Score Vectors. 137-149 - Deyu Ming, Daniel B. Williamson, Serge Guillas:
Deep Gaussian Process Emulation using Stochastic Imputation. 150-161 - Xiaojun Zheng, Simon Mak, Liyan Xie, Yao Xie:
PERCEPT: A New Online Change-Point Detection Method using Topological Data Analysis. 162-178 - Jie Guo, Hao Yan, Chen Zhang:
A Bayesian Partially Observable Online Change Detection Approach with Thompson Sampling. 179-191 - Wenlin Dai, Yan Song, Dianpeng Wang:
A Subsampling Method for Regression Problems Based on Minimum Energy Criterion. 192-205 - Xiaoyu Chen, Xiaoning Kang, Ran Jin, Xinwei Deng:
Bayesian Sparse Regression for Mixed Multi-Responses with Application to Runtime Metrics Prediction in Fog Manufacturing. 206-219 - Qian Xiao, V. Roshan Joseph, Douglas M. Ray:
Maximum One-Factor-At-A-Time Designs for Screening in Computer Experiments. 220-230 - Ying Jin, Shan Ba:
Toward Optimal Variance Reduction in Online Controlled Experiments. 231-242 - Xin Zan, Di Wang, Xiaochen Xian:
Spatial Rank-Based Augmentation for Nonparametric Online Monitoring and Adaptive Sampling of Big Data Streams. 243-256 - Parfait Munezero, Mattias Villani, Robert Kohn:
Dynamic Mixture of Experts Models for Online Prediction. 257-268 - Xingchen Liu, Juan Du, Zhisheng Ye:
A Covariate-Regulated Sparse Subspace Learning Model and Its Application to Process Monitoring and Fault Isolation. 269-280 - Yi Lian, Archer Y. Yang, Boxiang Wang, Peng Shi, Robert William Platt:
A Tweedie Compound Poisson Model in Reproducing Kernel Hilbert Space. 281-295 - Stan Lipovetsky:
Introduction to Math Olympiad Problems: by Michael A. Radin, Boca Raton, FL, Chapman and Hall/CRC Press, Taylor & Francis Group, 2021, 160 pp., $23.96 (pbk), ISBN 9780367544713. 296 - Nisar Ahmad Khan:
The Effect: An Introduction to Research Design and Causality: by Nisar Ahmad Khan, New York, Chapman and Hall/CRC, 2021, 646 pp., $23.99 (pbk), ISBN 978-1-032-12578-7. 297-298 - Peter Wludyka:
Principles of Biostatistics: by Marcello Pagano, Kimberlee Gauvreau, and Heather Mattie, CRC Press, Boca Raton, FL, 2022, 620 pp., $79.95, ISBN 9780429340512. 298-299 - Firdous Ahmad Mala:
Mathematical Analysis and Optimization for Economists: by Michael J. Panik, Chapman & Hall, 2021, 345 pp., $52.49 (HB), ISBN: 9780367759018. 300-301 - Firdous Ahmad Mala:
Number Systems: A Path into Rigorous Mathematics: by Anthony Kay, CRC Press, 2022, 317 pp., $130.00 (hcb), ISBN: 9780367180614. 301-302 - Stan Lipovetsky:
Handbook of Measurement Error Models: edited by Grace Y. Yi, Aurore Delaigle, and Paul Gustafson, Boca Raton, FL, Chapman & Hall/CRC Press, Taylor & Francis Group, 2021, xiv+577 pp., 33 B/W illustrations, $200.00 (hbk), ISBN 978-1-138-10640-6. 302-304
Volume 65, Number 3, July 2023
- Zhen Zhong, Kamran Paynabar, Jianjun (Jan) Shi:
Image-Based Feedback Control Using Tensor Analysis. 305-314 - Qingqing Zhai, Zhi-Sheng Ye:
A Multivariate Stochastic Degradation Model for Dependent Performance Characteristics. 315-327 - Naichen Shi, Raed Al Kontar:
Personalized Federated Learning via Domain Adaptation with an Application to Distributed 3D Printing. 328-339 - Christian H. Weiß, Murat Caner Testik:
Nonparametric Control Charts for Monitoring Serial Dependence based on Ordinal Patterns. 340-350 - Xinyi Lei, Zhicheng Chen, Hui Li:
Functional Outlier Detection for Density-Valued Data with Application to Robustify Distribution-to-Distribution Regression. 351-362 - Yongxiang Li, Yuting Pu, Changming Cheng, Qian Xiao:
A Scalable Gaussian Process for Large-Scale Periodic Data. 363-374 - Jinwei Yao, Xiaochen Xian, Chao Wang:
Adaptive Sampling for Monitoring Multi-Profile Data with Within-and-between Profile Correlation. 375-387 - Shin-Fu Tsai:
Dual-Orthogonal Arrays for Order-of-Addition Two-Level Factorial Experiments. 388-395 - Dennis K. J. Lin, Jianbin Chen:
Adaptive Order-of-Addition Experiments via the Quick-Sort Algorithm. 396-405 - Chunya Li, Xiaojun Cui, Shifeng Xiong:
Design and Analysis of Computer Experiments with both Numeral and Distributional Inputs. 406-417 - Chenglong Li, Xun Xiao:
On Censoring Time in Statistical Monitoring of Lifetime Data. 418-431 - Xiao Liu, Kyongmin Yeo:
Inverse Models for Estimating the Initial Condition of Spatio-Temporal Advection-Diffusion Processes. 432-445 - Stan Lipovetsky:
The Energy of Data and Distance Correlation,: Gabor J. Szekely and Maria L. Rizzo, Boca Raton, FL: CRC/CRC Press/Chapman & Hall/Taylor & Francis Group, 2023, xvii + 448 pp., $120.00 (hbk), 7 Color & 24 B/W Illustrations, ISBN 978-1-482-24274-4. 446-448 - Suprianto, Nur Alam:
Mathematical Modeling in Biology: A Research Methods Approach, 1st ed.: Shandelle M. Henson and James L. Hayward, Boca Raton, FL: Chapman and Hall/CRC Press, 2023, XXI + 315 pp., ISBN: 9781032208213 (hbk). Scope: Textbook. Level: Advanced Mathematics and Science Undergraduate Students and Graduate-Level Biology Students. 448-449 - Firdous Ahmad Mala:
Polynomial Methods and Incidence Theory: Adam Sheffer, Cambridge University Press, 2022, 263 pp., $64.99, ISBN: 9781108959988. 449-450 - Firdous Ahmad Mala:
Mathletics: How Gamblers, Managers, and Fans Use Mathematics in Sports, 2nd ed.: Wayne L. Winston, Scott Nestler, and Konstantinos Pelechrinis, Princeton University Press, 2022, 608 pp., $24.95, ISBN: 9780691177625. 450-451 - Aminatus Sa'adah:
Artificial Intelligence with Python: Teik Toe Teoh and Zheng Rong, Springer, 2022, 336 pp., EUR 16.99, ISBN 978-981-16-8615-3. 451-452
Volume 65, Number 4, October 2023
- Mengyang Gu, Kyle Anderson, Erika McPhillips:
Calibration of Imperfect Geophysical Models by Multiple Satellite Interferograms with Measurement Bias. 453-464 - Feng Xu, Lianjie Shu, Yanting Li, Binhui Wang:
Joint Diagnosis of High-Dimensional Process Mean and Covariance Matrix based on Bayesian Model Selection. 465-479 - Sean Ryan, Rebecca Killick:
Detecting Changes in Covariance via Random Matrix Theory. 480-491 - Jonathan W. Stallrich, Katherine Allen-Moyer, Bradley Jones:
D - and A -Optimal Screening Designs. 492-501 - Brian P. Weaver, Scott A. Vander Wiel:
Accelerated Event Times with Multiple Thresholds. 502-513 - Xin Wang, Xin Zhang, Zhengyuan Zhu:
Clustered Coefficient Regression Models for Poisson Process with an Application to Seasonal Warranty Claim Data. 514-523 - Shuoli Chen, Kejun He, Shiyuan He, Yang Ni, Raymond K. W. Wong:
Bayesian Nonlinear Tensor Regression with Functional Fused Elastic Net Prior. 524-536 - Qiang Heng, Eric C. Chi, Yufeng Liu:
Robust Low-Rank Tensor Decomposition with the L 2 Criterion. 537-552 - Gilberto Chávez-Martínez, Ankush Agarwal, Abbas Khalili, Syed Ejaz Ahmed:
Penalized Estimation of Sparse Markov Regime-Switching Vector Auto-Regressive Models. 553-563 - Xinchao Liu, Xiao Liu, Tulin Kaman, Xiaohua Lu, Guang Lin:
Statistical Learning for Nonlinear Dynamical Systems with Applications to Aircraft-UAV Collisions. 564-578 - Hang Yin, Abolfazl Safikhani, George Michailidis:
A General Modeling Framework for Network Autoregressive Processes. 579-589 - Andrew M. Thomas, Peter A. Crozier, Yuchen Xu, David S. Matteson:
Feature Detection and Hypothesis Testing for Extremely Noisy Nanoparticle Images using Topological Data Analysis. 590-603 - Stan Lipovetsky:
Luck, Logic, and White Lies: The Mathematics of Games; 2nd ed.Jörg Bewersdorff, translated by David Kramer, Boca Raton, FL: A.K. Peters/CRC Press, Taylor & Francis Group, 2021, xx + 548 pp., $ 47.96 (pbk), ISBN 9780367548414. 604-606 - Fajar Pitarsi Dharma, Moses Laksono Singgih, Hamdan S. Bintang:
AI, Machine Learning and Deep Learning a Security PerspectiveEdited by Fei Hu, Xiali Hei, Boca Raton, FL:CRC Press, 2023, 346 pp., 136 B/W Illustrations, GBP 99.99 (Hardback), ISBN 9781032034041, https://doi.org/10.1201/9781003187158. 606-607 - Aszani Aszani:
Machine Learning for Knowledge Discovery with R: Methodologies for Modeling, Inference, and PredictionKao-Tai Tsai, Boca Raton, FL: CRC Press, Taylor & Francis Group, LLC, 2022, xiii + 260 pp., $ 88.00, ISBN: 978-1-032-06536-6 (H). 607-609 - Irvanal Haq, Nila Lestari:
Statistical GenomicsBrooke Fridley and Xuefeng Wang, New York, NY: Humana, 2023, 377 pp., EUR 169.99, ISBN 978-1-0716-2986-4 (eBook). 609-610 - Enrique Garcia-Ceja:
A Criminologist's Guide to R: Crime by the NumbersJacob Kaplan, Boca Raton, FL: Chapman and Hall/CRC Press, Taylor & Francis Group, 2022, 432 pp., ISBN 9781032244075. 610-611 - Stan Lipovetsky:
Computer Age Statistical Inference: Algorithms, Evidence, and Data Science, Student ed.Bradley Efron and Trevor Hastie, UK: Cambridge University Press, 2021, xix + 491 pp., $ 39.99 (pbk), ISBN 978-1-108-82341-8. 611-613 - Abdulkadir Hussein:
Post-Shrinkage Strategies in Statistical and Machine Learning for High Dimensional DataPost-Shrinkage Strategies in Statistical and Machine Learning for High Dimensional Data, Syed Ejaz Ahmed, Feryaal Ahmed, and Bahadir Yüzbaşı, New York: Chapman and Hall/CRC Press, 2023, 408 pp., ISBN 9780367763442. 611 - Stan Lipovetsky:
Mathematics of The Big Four Casino Table Games: Blackjack, Baccarat, Craps, & RouletteMark Bollman, Boca Raton, FL: CRC Press/Chapman & Hall, Taylor & Francis Group, 2021, xi +353 pp., 43 B/W illustrations, $ 31.16 (pbk), ISBN 9780367740900. 613-614
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